Renal stone disease or renal calculus disease (also known as urolithiasis) is very common, and is increasing in prevalence. Based on National Health and Nutrition Examination Survey (NHANES) data, urolithiasis impacts approximately 1 in 11 people in the United States. NHANES data also demonstrated that obese and overweight individuals have a higher prevalence of kidney stones than normal weight individuals. This disease is associated with estimated recurrence rates of 50% in the first 5-10 years after an episode of renal colic, increasing to 75% within 20 years.
Because non-contrast helical CT (computed tomography) (NCCT) is rapid, accurate, and diagnoses other pathologies that mimic renal colic, NCCT has become a standard for detection and management of this disease and the use of NCCT has risen concomitantly with the increasing incidence of urolithiasis. NCCT rapidly performs a highly sensitive and specific diagnosis of urolithiasis, with the ability to both locate calculi and often characterize the composition of the calculi.
NCCT involves exposure to ionizing radiation in order to generate diagnostic images. This exposes patients to potential risks. Estimates reflecting current use suggest that 0.7-2% of future cancers in the United States may be caused by CT-associated radiation exposures. In one estimate from 2007 data, 29,000 future cancers may be attributable to diagnostic imaging examinations. This poses a significant dilemma for the management of patients with renal stone disease, particularly because this patient population is subject to high cumulative radiation exposure. Of additional significance is that medical radiation exposure is now responsible for the majority of effective dose incurred by the US population.
The patient population impacted by urolithiasis is often young and may require repeated CT scans. This poses a significant dilemma for balancing the diagnostic benefits against the risks associated with high cumulative radiation exposure. In this context, reducing the radiation dose of the NCCT scan as much as possible becomes an important goal, but reducing dose without affecting image quality has conventionally been difficult.
A methodology that has been receiving attention recently to reduce the dose associated with a CT scan is model-based iterative reconstruction (MBIR). The MBIR methodology offers tremendous potential for dose reduction. MBIR may provide enhanced image quality with less than 1 mSv dose per exam, whereas the mean dose for an NCCT scan of the abdomen is 8.5 mSv. Such a dose reduction is enabled by accounting for the statistical distribution of noise in the CT measurements together with the usage of non-linear constraints on the image pixel values. MBIR is currently under evaluation in the clinical environment and attractive results have been reported. Unfortunately, as discussed hereafter, MBIR is currently not a practical solution due to the extensive computational effort used for its implementation.
A fundamental strength of CT is fast patient throughput. In a clinical routine, CT exams often last less than 5 minutes, and images are produced at a rate of 30 to 40 images per second. By contrast, MBIR typically involves hours of reconstruction time for a single patient, despite various applied optimizations. An affordable and robust solution for clinical routine usage of MBIR may be delayed until major advances in computing hardware are achieved as well as in the design of the MBIR methodology.